A Concise Review of Cognitive Computing: Evolution and Applications

Abstract

Cognitive computing systems have significantly advanced over the past two decades, driven by big data proliferation and breakthroughs in machine learning, data mining, and natural language processing. These systems assist human expertise by analyzing complex data to identify relationships and offer solutions. However, cognitive systems' concepts and applications remain unclear to many, limiting adoption in industries like oil and gas. This review raises awareness of cognitive technology and its business benefits. The paper outlines the evolution and core concepts of cognitive systems to provide a foundational understanding. Subsequent sections explore their applications and future trends across various industries. Cognitive computing enhances human cognition by interpreting large datasets using machine learning, data mining, and NLP. It transforms data processing by integrating advanced analytics with machine learning models, helping industries manage vast data, uncover patterns, and improve decision-making. Cognitive systems offer flexibility and transparency, allowing users to grasp underlying assumptions, data sources, and hypotheses. Hardware innovations, such as neuromorphic and quantum computing, are expected to boost performance, enabling cognitive systems to handle extensive data and respond contextually in real time. The future promises transformative advances in real-time processing and machine learning, driving change in healthcare (predictive diagnostics and personalized medicine), oil and gas (exploration and production optimization), sports (performance analytics and injury prediction), and security (enhanced threat detection and response).